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Updated 4 weeks ago

text-embedding

Text Embedding with Transformers

author: Jael Gu


Description

A text embedding operator takes a sentence, paragraph, or document in string as an input and output an embedding vector in ndarray which captures the input's core semantic elements. This operator is implemented with pre-trained models from Huggingface Transformers.


Code Example

Use the pre-trained model 'distilbert-base-cased' to generate a text embedding for the sentence "Hello, world.".

Write the pipeline:

import towhee

towhee.dc(["Hello, world."]) \
      .text_embedding.transformers(model_name="distilbert-base-cased")


Factory Constructor

Create the operator via the following factory method:

text_embedding.transformers(model_name="bert-base-uncased")

Parameters:

model_name: str

The model name in string. The default model name is "bert-base-uncased".

Supported model names:

Albert
  • albert-base-v1
  • albert-large-v1
  • albert-xlarge-v1
  • albert-xxlarge-v1
  • albert-base-v2
  • albert-large-v2
  • albert-xlarge-v2
  • albert-xxlarge-v2
Bart
  • facebook/bart-large
Bert
  • bert-base-cased
  • bert-large-cased
  • bert-base-multilingual-uncased
  • bert-base-multilingual-cased
  • bert-base-chinese
  • bert-base-german-cased
  • bert-large-uncased-whole-word-masking
  • bert-large-cased-whole-word-masking
  • bert-large-uncased-whole-word-masking-finetuned-squad
  • bert-large-cased-whole-word-masking-finetuned-squad
  • bert-base-cased-finetuned-mrpc
  • bert-base-german-dbmdz-cased
  • bert-base-german-dbmdz-uncased
  • cl-tohoku/bert-base-japanese-whole-word-masking
  • cl-tohoku/bert-base-japanese-char
  • cl-tohoku/bert-base-japanese-char-whole-word-masking
  • TurkuNLP/bert-base-finnish-cased-v1
  • TurkuNLP/bert-base-finnish-uncased-v1
  • wietsedv/bert-base-dutch-cased
BertGeneration
  • google/bert_for_seq_generation_L-24_bbc_encoder
BigBird
  • google/bigbird-roberta-base
  • google/bigbird-roberta-large
  • google/bigbird-base-trivia-itc
BigBirdPegasus
  • google/bigbird-pegasus-large-arxiv
  • google/bigbird-pegasus-large-pubmed
  • google/bigbird-pegasus-large-bigpatent
CamemBert
  • camembert-base
  • Musixmatch/umberto-commoncrawl-cased-v1
  • Musixmatch/umberto-wikipedia-uncased-v1
Canine
  • google/canine-s
  • google/canine-c
Convbert
  • YituTech/conv-bert-base
  • YituTech/conv-bert-medium-small
  • YituTech/conv-bert-small
CTRL - ctrl
DeBERTa
  • microsoft/deberta-base
  • microsoft/deberta-large
  • microsoft/deberta-xlarge
  • microsoft/deberta-base-mnli
  • microsoft/deberta-large-mnli
  • microsoft/deberta-xlarge-mnli
  • microsoft/deberta-v2-xlarge
  • microsoft/deberta-v2-xxlarge
  • microsoft/deberta-v2-xlarge-mnli
  • microsoft/deberta-v2-xxlarge-mnli
DistilBert
  • distilbert-base-uncased
  • distilbert-base-uncased-distilled-squad
  • distilbert-base-cased
  • distilbert-base-cased-distilled-squad
  • distilbert-base-german-cased
  • distilbert-base-multilingual-cased
  • distilbert-base-uncased-finetuned-sst-2-english
Electral
  • google/electra-small-generator
  • google/electra-base-generator
  • google/electra-large-generator
  • google/electra-small-discriminator
  • google/electra-base-discriminator
  • google/electra-large-discriminator
Flaubert
  • flaubert/flaubert_small_cased
  • flaubert/flaubert_base_uncased
  • flaubert/flaubert_base_cased
  • flaubert/flaubert_large_cased
FNet
  • google/fnet-base
  • google/fnet-large
FSMT
  • facebook/wmt19-ru-en
Funnel - funnel-transformer/small - funnel-transformer/small-base - funnel-transformer/medium - funnel-transformer/medium-base - funnel-transformer/intermediate - funnel-transformer/intermediate-base - funnel-transformer/large - funnel-transformer/large-base - funnel-transformer/xlarge-base - funnel-transformer/xlarge
GPT
  • openai-gpt
  • gpt2
  • gpt2-medium
  • gpt2-large
  • gpt2-xl
  • distilgpt2
  • EleutherAI/gpt-neo-1.3B
  • EleutherAI/gpt-j-6B
I-Bert
  • kssteven/ibert-roberta-base
LED
  • allenai/led-base-16384
MobileBert
  • google/mobilebert-uncased
MPNet
  • microsoft/mpnet-base
Nystromformer
  • uw-madison/nystromformer-512
Reformer
  • google/reformer-crime-and-punishment
Splinter
  • tau/splinter-base
  • tau/splinter-base-qass
  • tau/splinter-large
  • tau/splinter-large-qass
SqueezeBert
  • squeezebert/squeezebert-uncased
  • squeezebert/squeezebert-mnli
  • squeezebert/squeezebert-mnli-headless
TransfoXL
  • transfo-xl-wt103
XLM
  • xlm-mlm-en-2048
  • xlm-mlm-ende-1024
  • xlm-mlm-enfr-1024
  • xlm-mlm-enro-1024
  • xlm-mlm-tlm-xnli15-1024
  • xlm-mlm-xnli15-1024
  • xlm-clm-enfr-1024
  • xlm-clm-ende-1024
  • xlm-mlm-17-1280
  • xlm-mlm-100-1280
XLMRoberta
  • xlm-roberta-base
  • xlm-roberta-large
  • xlm-roberta-large-finetuned-conll02-dutch
  • xlm-roberta-large-finetuned-conll02-spanish
  • xlm-roberta-large-finetuned-conll03-english
  • xlm-roberta-large-finetuned-conll03-german
XLNet
  • xlnet-base-cased
  • xlnet-large-cased
Yoso
  • uw-madison/yoso-4096


Interface

The operator takes a piece of text in string as input. It loads tokenizer and pre-trained model using model name. and then return text embedding in ndarray.

Parameters:

text: str

​ The text in string.

Returns:

numpy.ndarray

​ The text embedding extracted by model.

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